Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Jan Hendrik Witte"'
Publikováno v:
BIS
In this paper, the deep learning instance segmentation architectures DetectoRS, SOLOv2, DETR and Mask R-CNN were applied to data from the field of Pig Precision Livestock Farming to investigate whether these models can address the specific challenges
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09ea458f9e8b9425c83dba67aadcb147
https://doi.org/10.52825/bis.v1i.59
https://doi.org/10.52825/bis.v1i.59
Autor:
Jan-Hendrik Witte, Jorge Marx Gómez
Publikováno v:
Proceedings of the Annual Hawaii International Conference on System Sciences.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b04541a7d7807a8b5fdbcda95641dce
https://doi.org/10.24251/hicss.2022.140
https://doi.org/10.24251/hicss.2022.140
Autor:
Jan-Hendrik Witte
Publikováno v:
Progress in IS ISBN: 9783031154195
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa60032a9dc3e8eff581ea35873df24c
https://doi.org/10.1007/978-3-031-15420-1_10
https://doi.org/10.1007/978-3-031-15420-1_10
Publikováno v:
Progress in IS ISBN: 9783031154195
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d04a8ad7545992ea9cc7da9f70c0b059
https://doi.org/10.1007/978-3-031-15420-1_19
https://doi.org/10.1007/978-3-031-15420-1_19
Autor:
Jan Hendrik Witte
Publikováno v:
Wilmott. 2016:60-67
Studying binomial and Gaussian return dynamics in discrete time, we show how excess volatility can be traded to create growth. We test our results on real-world data to confirm the observed model phenomena while also highlighting the implicit risks.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37d5aae795cf3b6a4cd172e5832e01dd
https://doi.org/10.1002/wilm.10511
https://doi.org/10.1002/wilm.10511
Autor:
Jan Hendrik Witte, Nicholas G. Polson
Publikováno v:
CHANCE. 28:27-31
Richard Bellman's Principle of Optimality, formulated in 1957, is the heart of dynamic programming, the mathematical discipline which studies the optimal solution of multi-period decision problems. In this paper, we look at the main trading principle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c74a0bfa5415ad001ca5dc1ba7ca8b3
https://doi.org/10.1080/09332480.2015.1016846
https://doi.org/10.1080/09332480.2015.1016846
This article combines various methods of analysis to draw a comprehensive picture of penalty approximations to the value, hedge ratio, and optimal exercise strategy of American options. We use matched asymptotic expansions to characterize the boundar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a58d0dc5a60173f88a6e86711b033a9
https://ora.ox.ac.uk/objects/uuid:6c294df4-210d-460d-aa71-dff0536f8c8e
https://ora.ox.ac.uk/objects/uuid:6c294df4-210d-460d-aa71-dff0536f8c8e
Autor:
Jan Hendrik Witte, Christoph Reisinger
Publikováno v:
SIAM Journal on Numerical Analysis. 49:213-231
We present a simple and easy to implement method for the numerical solution of a rather general class of Hamilton-Jacobi-Bellman (HJB) equations. In many cases, the considered problems have only a viscosity solution, to which, fortunately, many intui
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::867bd5bd57b1544e54f2eb29ec1f85d1
https://doi.org/10.1137/100797606
https://doi.org/10.1137/100797606
Publikováno v:
Mathematical Methods of Operations Research. 81(1)
We consider a class of discrete time stochastic control problems motivated by some financial applications. We use a pathwise stochastic control approach to provide a dual formulation of the problem. This enables us to develop a numerical technique fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27ed5e2b492c8145f44cff2e3d3667b3
http://ora.ox.ac.uk/objects/uuid:0bcf30e5-fec3-4599-86c0-8e8aabfbd1fb
http://ora.ox.ac.uk/objects/uuid:0bcf30e5-fec3-4599-86c0-8e8aabfbd1fb
Autor:
Jan Hendrik Witte
Studying Binomial and Gaussian return dynamics in discrete time, we show how excess volatility can be traded to create growth. We test our results on real world data to confirm the observed model phenomena while also highlighting implicit risks.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4491c9536c2a651316686347e0e86471